Decoding Complex Event Processing in Simpler Terms

Complex event processing allows an organization to gain accurate insights and use them to shape its strategies and decisions.

This effective technique helps you see the bigger picture in the form of high-level events extracted from massive data streams.

This means you can easily detect threats and opportunities and respond to them in no time.  

Ultimately, it helps you improve your operations, beat the competition, and stay secure.

In this article, I’ll talk about complex event processing, its benefits and use case, and other essential details.

Let’s start!

What Is Complex Event Processing?

Complex event processing (CEP) involves a set of technologies, techniques, and concepts to process real-time events from data streams upon their arrival and extract useful information from them.

CEP is event-driven since the event data received triggers the computation. Here, the incoming event data is refined into a higher-level or “complex” and useful event data. This process not only encompasses data processing but also aggregating, analyzing, and tracking data streams to gain insights in real-time.

Complex event processing aims to identify meaningful events like threats, opportunities, etc. in real-time and respond immediately to them.

To further simplify the CEP, let’s understand how it’s named.

Event: Events keep happening throughout an organization, which could be both high-level(complex and more important) and low-level (simpler and less important). An event could be social media messages and posts, text messages, phone calls, news items, orders placed, sales leads, stock market feeds, weather reports, spikes in temperature, traffic situations, online threats, transactions, and more.

Complex events: These are high-level events that are critical for an organization. These events could be authorized access to an application or data, password change, fund transfer, buying a stock, etc. You need to respond to these events immediately and ensure the safety of your data and resources.

Processing: aggregating, analyzing, and tracking complex data in real-time to make meaningful conclusions.

CEP is applied in continuous-intelligence services and applications that are highly demanding nowadays and helps improve real-time decision-making and gain situational awareness. CEP is also used in sectors like stock market trading, internet operations, mobile devices, fraud detection, government intelligence, transportation, and more.        

Some CEP applications are TIBCO Streaming, IBM event streams, Oracle SOA Suite, Astra Streaming, Aerospike, and more.                                                                                             

How Does CEP Work?

CEP is like a toolkit to extract meaningful information from data streams. Usually, two data streams illustrate the same reality in different ways. It implements domain knowledge in multiple data sources to understand a situation in terms of complex events and high-level concepts.

For example, CEP can be utilized in cybersecurity. Suppose you receive an alert regarding unauthorized system access, and then you see a message of an unknown transaction. If you combine these two events with your knowledge of cybersecurity, you can conclude that online fraud is likely to be happening.  

CEP is developed to infer complex events like them from raw information using concepts and patterns. This technique helps you analyze and correlate other simpler events to uncover complex events. It aims to find out meaningful details that businesses can use to make relevant, informed decisions.

Complex event processing uses an event-driven architecture where predefined events trigger data processing operations. This is in contrast to traditional models, where you need to process each data object continuously to produce results.

Here, an event-driven model continuously processes data objects but generates results only for user-defined events. This architecture has three components:

• An event
• An event-processing engine
• The action

You will need to define events and register them using the event processing engine. Then, you will need to find data and map it systematically to events. Now, the engine identifies the events and maps them based on the defined criteria. The system will ingest data variables in different formats and map them into some predefined events according to your use case.

Once done, users can define particular actions for these events. An action is a function that is created to receive incoming events like alerts.

So, in the next step, the event engine monitors the data streams for defined events. Once it detects these events, it forwards them to users and triggers an action for event processing.

CEP Techniques

CEP uses various techniques, including:

• Event filtering: As soon as the data is received, you can filter events. It takes place at the beginning of complex event processing and can be done at the end as well when the complex events are processed or discovered. Doing this helps you eliminate unwanted events and select relevant events for a specific purpose. You can apply filters such as severity, category, assigned users, etc.

• Event-pattern detection: This technique helps you detect certain patterns in a data stream, which might lead you to a complex event.
• Event abstraction: In this technique, you can derive a concept from the aggregated and analyzed data. This concept can act as a collective idea for other concepts, connecting related concepts as a field or group.  
• Event aggregation & transformation: Event aggregation is a technique that is performed in the initial stages of CEP. It’s when you start collecting and aggregating events from data streams. It paves the way for subsequent processes like analysis, tracking, and so on. Similarly, event transformation involves turning unstructured, raw streams of information into relevant, important data.
• Event hierarchy modeling: In this technique, event data is organized in some sort of hierarchy to enable easier data analysis and processing. 
• Event relationship detection: This process involves detecting relationships between events based on timing, membership, causality, etc. This helps you filter out related events and proceed forward with the bigger concept.

Benefits of CEP

Complex event processing offers many benefits to users. Some of them are:

Gain High-level Insights

With CEP, you can synthesize business data from domain knowledge and raw data. it will allow you to organize data into high-level events based on different contexts, time frames, and relationships within that data.

Thus, you can use high-level insights to understand crucial things about your operations, business, market, customers, and competitors.

This will help you make better business strategies and create more useful products and services for your customers. In addition, you can stay ahead of your competitors and dominate the market.

Effective Incident Response

CEP enables organizations to proactively respond to threats in real-time. This becomes possible by analyzing high-level data from raw, unstructured information from different sources.

Thus, you can deter the threats quickly when you still have time and keep your data and systems safe from online attacks.

Horizontal Scalability

Since you can process a high data volume with efficiency, you can also scale your computing resources as and when needed. Open-source services like Kubernetes and public clouds like AWS can terminate and replicate processing nodes quite easily. Thus, you can host your CEP applications on these infrastructures and scale your resources easily and quickly based on demands.

High Performance

Distributing data among employee/worker nodes is crucial in a Big Data framework. CEP helps partition and distribute data effectively among these nodes. This allows these frameworks to achieve higher performance by implementing data processing logic in parallel. This means more data can be processed simultaneously, which in turn, increases efficiency.

Low Latency

CEP engines are known for low-latency data processing and produce data in real-time that is up-to-date and relevant. It also strives to minimize higher IO costs by maintaining in-memory data to the minimum.

Improved Business Logic

As CEP helps you gain meaningful information out of raw data, you can use this data to improve your business logic. You can assess various aspects of your business, including the overall performance, strategies, employee contributions, clientele, revenue, and future scopes. This way, you can find inefficiencies faster and work on improving your business logic which can produce better results.

Better Predictions

By carefully analyzing the collected data with the help of CEP, it becomes easier for you to determine the direction in which your business is going. You can make better predictions using the insights gained and plan your business accordingly. This can help increase your chances of success.

Saves Time

Every business deals with a massive volume of data, but not all is valuable. Many of these data will be irrelevant, outdated, incomplete, and unuseful for your business. Also, many smaller data will hint at a single idea or event.

At this time, you need a system that can segregate quality data and combine similar data to extract meaningful information. CEP does exactly that.

CEP vs. ESP

Complex event processing (CEP) and event stream processing (ESP) might look similar and can sometimes be used interchangeably. However, they are not identical.

Traditional event streaming involves a single data stream arriving at a given time. Simply put, it collects one event at a time, like a click or transaction occurring on a site. It then analyzes this event and processes it to enable you to respond to it.

For example, an ESP solution can analyze a pricing data stream to allow the user to decide whether they want to sell or buy a stock.

In general, ESP tools don’t include event hierarchy or causality.

On the other hand, complex data processing is more like an advanced version of ESP. It collects multiple data streams to detect a particular event. It also involves complex event detection and processing.

Use Cases of CEP

You can apply complex event processing in various industries and use cases. In general, it’s used in cases involving large event volumes and low latency requirements (preferably in milliseconds). Some use cases are:

Fraud Detection and Prevention

Complex event processing capabilities allow businesses and institutions to detect fraudulent activities by monitoring various patterns and tracking events in real-time. For example, you can combine new device logins with password changes to design a complex event.

This will help you flag suspicious or fraudulent activity so you can take preventive actions on time and deter online threats. You can also combine several fraud alerts into a high-level event to detect a system-wide online breach.

In addition, CEP is used in firewall systems to detect anomalies with the help of machine learning.

Highly regulated industries like banks, healthcare institutions, defense, etc., can use CEP to identify and mitigate threats and keep their data and operations safe.

Hardware Design

CEP was initially introduced for designing computer chips. This enables engineers to figure out low-level events occurring in the real physical hardware based on the chip’s instructions and register-level design.

Marketing

CEP can be highly useful in the marketing industry. Businesses can use it to understand their market and customers and design effective marketing strategies to draw more visitors to their offerings. It also helps them with targeted ads based on viewers’ profiles.

Personalization is crucial for modern customers instead of vague, random products or services. CEP helps you with that by letting you track and analyze customers’ buying behavior.

For example, e-commerce businesses can utilize CEP to provide personalized recommendations in real-time based on their shopping habits, holidays, seasons, social network activities, and GPS data. A great thing about CEP is that it can combine multiple data sources with historical data to provide deeper insights.

Predictive Analytics

CEP is a part of the predictive analytics ecosystem since you can aggregate and analyze massive data volumes from various sources and make predictions.

Combining different events from social media sites, sales, GPS streams, etc., you will be able to predict crucial events that can impact your business. You can also make strategies to align with those impacts and stay relevant in the industry.

For example, when the covid-19 struck the world, businesses could analyze massive data from networking sites like Twitter and pharmacy sales to predict events. It could help them mold their offerings in such a way that can help their consumers in this scenario.

IoT

Complex event processing can be utilized in the Internet of Things (IoT). As it combines data from different sources, it can transform the whole process of collecting IoT-based sensor streams to enable real-time monitoring, troubleshooting issues, and analytics.

Example: Combining data from fans, lights, alarms, heating devices, and other devices in a smart building you have rented, you can predict how the occupants are using the resources and optimize usage.  

Stock Market Trading

Using a CEP-based application or service, you can determine the latest stock prices, find patterns, and correlate them against those patterns. It will enable you to decide whether you want to trigger a selling or buying decision. This increases your chances of success compared to the one where you randomly make decisions or perform computations yourself, which is time taking and may involve errors.

Predictive Maintenance

You can use CEP in predictive maintenance for large objects like airplanes and windmills and also for sensors in a manufacturing facility. By regularly monitoring and analyzing data, you can detect patterns indicating the need for maintenance or shutting down equipment, machine, or a system.

Other Uses

• CEP is also used in autonomous vehicles. The sensors used in them can deliver data to enable the CEP system integrated into the car to recognize start or stop signs. The system can also measure the distance and road moisture to adjust the car’s acceleration.
• In supply chain management, CEP is used to calculate inventory in real time based on (Radio Frequency Identification) RFID.
• Operational Intelligence (OI) services use CEP to provide better insights into operations by analyzing event data and live feeds and correlating the data with historical data.
• CEP is used in business process management (BPM) to align and optimize for the operational environment.

Conclusion

Complex event processing (CEP) lets you gain meaningful information and make better planning and decisions by collecting, organizing, analyzing, and tracking raw data from multiple sources.

Thus, CEP is useful in various scenarios such as digital marketing, stock market trading, detecting and preventing fraud, making accurate predictions, and more.

You may also read advanced analytics and its importance for your business.